"format": "time_series",
          "hide": false,
          "intervalFactor": 2,
          "legendFormat": "Total (k8s)",
          "refId": "A",
          "step": 2
        }
      ],
      "title": "Memory",
      "type": "timeseries"
    },
    {
      "datasource": {
        "type": "prometheus",
        "uid": "${datasource}"
      },

### Step 1: Ensure Elasticsearch minimum requirements are met

MinIO requires a 5.x series version of Elasticsearch. This is the latest major release series. Elasticsearch provides version upgrade migration guidelines [here](https://www.elastic.co/guide/en/elasticsearch/reference/current/setup-upgrade.html).

### Step 2: Add Elasticsearch endpoint to MinIO

You could also use it to generate code automatically, for clients that communicate with your API. For example, frontend, mobile or IoT applications.

## Recap, step by step

### Step 1: import `FastAPI`

```Python hl_lines="1"
{!../../../docs_src/first_steps/tutorial001.py!}
```

`FastAPI` is a Python class that provides all the functionality for your API.

	return nil
}

// Step takes a string provided from a server (or just an empty string for the
// very first conversation step) and attempts to move the authentication
// conversation forward.  It returns a string to be sent to the server or an
// error if the server message is invalid.  Calling Step after a conversation
// completes is also an error.
func (x *XDGSCRAMClient) Step(challenge string) (response string, err error) {

  // followed by `TFE_ContextAsyncWait` to clear pending operations. It will be
  // used to cancel all other operations if any fails.
  //
  // Set step_id to configure the step id used for rendezvous creation. step id
  // of value -1 is reserved for global rendezvous and should not be set here.
  void StartExecute(TFE_Context* context,
                    const std::vector<ParallelTensor*>& inputs,

        Doc(
            """
            'Whitelist' validation step. The parameter field will be the single one
            allowed by the alias or set of aliases defined.
            """
        ),
    ] = None,
    serialization_alias: Annotated[
        Union[str, None],
        Doc(
            """
            'Blacklist' validation step. The vanilla parameter field will be the

      val lengthByteCount = (lengthBitCount + 7) / 8
      sink.writeByte(0b1000_0000 or lengthByteCount)
      for (shift in (lengthByteCount - 1) * 8 downTo 0 step 8) {
        sink.writeByte((length shr shift).toInt())
      }
    }

    // Write the payload.
    sink.writeAll(content)
  }

  /**

namespace gradients {

using namespace std;

// ================== Helper functions =================

// Fills data with values [start,end) with given step size.
void Range(vector<int32_t>* data, int32_t start, int32_t end,
           int32_t step = 1) {
  for (int32_t i = start; i < end; i += step) {
    (*data)[i] = i;
  }
}

// Fills out_dims with the dimensions of the given tensor.
void GetDims(const TF_Tensor* t, int64_t* out_dims) {

be used to select a different 'environment'.

## Installing

The new installer is intended to be modular and very explicit about what is installed. It has
far more steps than the Istio installer - but each step is smaller and focused on a specific
feature, and can be performed by different people/teams at different times.

It is strongly recommended that different namespaces are used, with different service accounts.

      append("\n")
    }
  }
}

internal fun commonHeadersGet(
  namesAndValues: Array<String>,
  name: String,
): String? {
  for (i in namesAndValues.size - 2 downTo 0 step 2) {
    if (name.equals(namesAndValues[i], ignoreCase = true)) {
      return namesAndValues[i + 1]
    }
  }
  return null
}

internal fun Headers.Builder.commonAdd(
  name: String,
  value: String,